AI Automation Engineer/ Sr. AI Automation Engineer

Applied Systems, Inc.•,

1d•$80,000 - $160,000•Remote

About The Position

We’re searching for a Sr. AI Automation Engineer to join our IT AI Automation team in Remote role. This full-time role reports to Manoj Matthew and will help harden, deploy, run, and partner on AI at scale across the business. The IT AI Automation team partners with business units that build proofs of concept, then hardens and ships those solutions to production on a shared, governed GCP platform with authentication, CI/CD, secrets management, and monitoring. To keep us headed in the right direction, we’re looking for people who understand winning is a team sport, who value and seek to learn from our team’s diverse experiences and backgrounds, who welcome a challenge and take risks in the pursuit of creating better outcomes for our customers, and who can, at any given time, step back to laugh and have some fun.

Requirements

5+ years building and shipping production software or data/automation applications.
Strong Python skills, solid SQL experience, and comfort working with real, governed data schemas.
Hands-on cloud experience, preferably with GCP, including deploying and operating services.
Working knowledge of production fundamentals, including authentication/identity, secrets management, CI/CD, logging, and monitoring.
Experience integrating with third-party APIs and SaaS platforms.
Ability to work directly with business stakeholders and translate evolving requirements into shipped, supportable software.

Nice To Haves

Experience building LLM-powered applications and agents, including tool/function calling, retrieval, and agentic workflows.
Experience with LLM evaluation and observability tooling such as LangSmith, Langfuse, Braintrust, or equivalents.
Familiarity with retrieval pipelines and vector databases such as Vertex AI Vector Search, Pinecone, or pgvector.

Responsibilities

Build and deploy micro-apps with the business. Partner directly with business owners to take proofs of concept from “works on my machine” to production, including dashboards, reconciliation and reporting tools, internal apps, chatbots, and support agents.
Build AI integrations and agents. Design, build, and publish reusable Claude skills and agents across the company, including retrieval and tool-calling pipelines grounded in company data.
Integrate AI into existing business systems. Build integrations across systems such as Salesforce/Agentforce, Slack, NetSuite, and SQL data sources.
Harden applications for production. Apply authentication, access controls, secrets management, CI/CD, logging, monitoring, token and cost controls, and version control for prompts and agent configurations.
Operate apps on a governed GCP platform. Run and maintain applications on shared infrastructure, respond to issues, and support the apps the business depends on.
Automate secure software maintenance. Build and maintain tooling that auto-updates software libraries and dependencies so deployed apps stay patched and secure.
Evaluate and monitor AI quality. Build evaluations, regression tests, and quality monitoring for shipped apps and agents, including task completion, retrieval quality, drift, and system uptime.